Instructions to use jonl521/modeling_simple with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use jonl521/modeling_simple with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("jonl521/modeling_simple", device_map="auto") - Notebooks
- Google Colab
- Kaggle
modeling_simple / .venv /lib /python3.14 /site-packages /numpy /random /_bounded_integers.cpython-314-darwin.so
Download .venv/lib/python3.14/site-packages/numpy/random/_bounded_integers.cpython-314-darwin.so from jonl521/modeling_simple: direct link, hf CLI and curl.
- Browser
- Download file 296 kB
-
https://huggingface.co/jonl521/modeling_simple/resolve/main/.venv/lib/python3.14/site-packages/numpy/random/_bounded_integers.cpython-314-darwin.so
- Command line
-
hf download hf://jonl521/modeling_simple/.venv/lib/python3.14/site-packages/numpy/random/_bounded_integers.cpython-314-darwin.so
-
curl -L -o _bounded_integers.cpython-314-darwin.so https://huggingface.co/jonl521/modeling_simple/resolve/main/.venv/lib/python3.14/site-packages/numpy/random/_bounded_integers.cpython-314-darwin.so
296 kB
- Xet hash:
- e111c359fc96c1f8f453a398221bb4768f8f80465df2cdaab973b8e867d214d7
- Size of remote file:
- 296 kB
- SHA256:
- c0a434748f30a816842e43ca04565cfc078deccd958527a5ebf684f70f167af6
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